DEVELOPMENT... OpenML
Run
156945

Run 156945

Task 3608 (Supervised Classification) fri_c4_500_100 Uploaded 11-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I10
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

22 Evaluation measures

Area under ROC curve
0.9242
Per class
F measure
0.8472
Per class
Kappa
0.6879
KB relative information score
268.0387
Mean absolute error
0.2444
Mean prior absolute error
0.4913
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8481
Per class
Predictive accuracy
0.848
Prior entropy
0.9875
Recall
0.848
Per class
Relative absolute error
0.4975
Root mean prior squared error
0.4956
Root mean squared error
0.3314
Root relative squared error
0.6686
SciMark benchmark
929.566
UserCPU time millis
120
UserCPU time millis training
120